Most Family Physicians are now participating in Maintenance of Certification (MOC), measuring and reporting quality measures from limited patient samples before and after a quality improvement effort (Part IV requirement). It is time to take next steps towards broader and more regular assessment of quality, and to simultaneously reduce reporting burden. This intention is consistent with AHRQ's aims for HIT and Quality and with those of the Office of the National Coordinator for Health Information Technology (Direct Project and Nationwide Health Information Network Exchange). The objective of the TRADEMARQ study is to make quality reporting a byproduct of ambulatory care and ongoing quality improvement. It has four aims: 1) To test the capacity for exchange of whole-panel, family physician quality measures from clinical networks; 2) To study whether viewing quality measures and comparison to peers will affect the types of self-assessment modules and quality improvement efforts that are chosen by family physicians (randomized); 3) To study whether viewing quality measures and comparison to peers will influence the degree of change in outcomes after quality improvement efforts (randomized) We have developed partnerships with three clinical systems for this study: Kaiser Permanente Colorado, the Oregon Community Health Information Network (now OCHIN), and the South East Texas Medical Associates (SETMA). All three use standardized, physician-level quality measures and are willing to test ways to securely share these. We will develop project leadership and secure data exchange pathway to all three entities to iteratively test means of automating direct transmission of family physician measures, exploring both technical and legal solutions (Aim1). For Aim 2, physicians will be randomized within system to exposure to their measures and comparisons to peers before or after they choose their self-assessment and quality improvement projects. Within each randomization arm, we will conduct a formal correlation analysis between SAM and Part IV selection and quality measures using hierarchical logistic regression adjusting for propensity of providers to select a SAM / Part IV. For Aim 3, we will assess changes in crude rates of quality measures from baseline to study completion using a difference in difference analysis which controls for physician characteristics via the propensity score calculated for Aim 2 and a longitudinal hierarchical logistic regression model fit to account for dependence of observations. This application is the first stage of three to which the ABFM has made a $2 million commitment. The partnership with AHRQ will help support our collaborators and offers critical federal data protections for the study.